Body condition scoring is a method of evaluating fatness or thinness in cows according to a scale, e.g. a five-point scale, where a score of one denotes a very thin cow, while five denotes an excessively fat cow. Research and field experiments have shown that body condition influences productivity, re-production, health and longevity. Thus, thinness or fatness can indicate underlying nutritional deficiencies, health problems, or improper herd management. As a mean to detect problems within the herd, body condition scoring is a good aid in improving the health and productivity of a dairy herd, when done on a regular basis, thus acting as an efficient tool in good herd management. Body condition scoring is better for monitoring body energy reserves than body weight. Body weight can change due to changes in body fat, frame size, gut size, udder size, pregnancy status, and intake of food and water.
The body condition of a normal, healthy, cow fluctuates over the lactation periods, as can be seen in FIG. 1. At calving, a recommended body condition score may be 3.25 to 3.75 or somewhat lower. At early lactation the cow increases the production of milk until peak milk production is reached. During this period the cow uses its body reserves to get the energy necessary as food intake will lag behind requirements in the first six to eight weeks of lactation. The goal is to have a loss in the body condition of 0.5 to 0.75 in early lactation. At mid-lactation the body condition score should slowly increase to reach the same recommended value of 3.25 to 3.75 as at calving at the end of late lactation. It is important not to attempt to correct the body condition of the cow during the dry period as this will affect the weight of the calf more than the weight of the cow.
Over-conditioning, or fatness, usually begins during the last three to four months of lactation, when milk production has decreased, but grain and total nutrients levels have not been reduced accordingly. At the time of calving, a cow with a body condition score over 4.0 often results in reduced feed intake and increased incidence of peripartum problems and other difficulties at calving. A fat cow is more susceptible to metabolic problems and infections. Over-conditioned cows tend to have problems with retained placenta, gastroparesis leading to calcium deficit, fat cow syndrome, fatty liver and mastitis. They might even collapse under their excessive weight.
Under-conditioning, or thinness, occurs when a cow has been ill for a longer period, or if not enough energy has been added to the diet during mid- and late lactation. Under-conditioning at calving with a body condition score of less than 3.0 often results in lower peak milk yield and less milk for the entire lactation. It is a health risk in the early lactation when the cow uses much of its body reserves. Also cows should not lose more than 1.0 body score during early lactation as excessive loss of body condition in early lactation has been shown to reduce reproductive efficiency. Under-conditioning can frequently lower production and milk fat levels because of insufficient energy and protein reserves. Thin cows often do not show heat or conceive until they start to regain—or at least maintain—body weight. In feeding these animals, care must be taken to maintain production while increasing body reserves.
A five-point scoring system was developed to measure the relative amount of this subcutaneous body fat. Most body condition scoring systems in dairy cattle use the five-point scoring system with quarter point increments. Instructions for a body condition scoring system have been devised to assess the body condition of a dairy cow at any point during the production cycle. For accurate scoring, both visual and tactile appraisals of back and hind quarters are necessary. The parts considered are the thoracic and lumbar regions of the vertebral column (chine, loin and rump), spinous processes (loin), tuber sacrale (hooks), tuber ischii (pin bones), and anterior coccygeal vertebrae (tail head) which are shown in FIG. 3. A single factor may be misleading; however, all factors considered together provide an accurate score. Each condition score was assessed by the criteria simplified in FIG. 4.
Although the benefits of regular body condition scoring are intuitive to most dairy producers, nutritionists, and consultants, relatively few dairy farms have incorporated it as a part of their dairy management strategy. There are many reasons for the lack of adoption of this system, mostly related to its subjectivity, costs and time commitment required. It is hardly practical in a computerized herd management system.
Dairy scientists have not yet developed the necessary objective research to be able to advice farmers properly. Therefore, there is a need to develop methods to determine the body condition score of individual cows in an automatic manner, which would be more cost effective, objective and easy to connect with data from a herd management system.
Pompe V. J deGraaf, R. Semplonious, and J. Meuleman, “Automatic body condition scoring of dairy cows: Extracting contour lines” Book of Abstracts, 5th European Conference on Precision Agriculture, 2nd European Conference on Precision Livestock Farming, 243-245, 2005 used black-and-white photography and a line laser to collect a series of images from the rear of the cow. A three-dimensional analysis of the images provided an outline of the left pin, left hook, and tailhead. No statistical analysis comparing image analysis with BCS was reported.
T. Leroy, J.-M-Aerts, J. Eeman, E. Maltz, G. Stojanovski, and D. Berckmans, “Automatic determination of body condition score of dairy cows based on 2D images” Precision Livestock Farming 05: 251-255, 2005 used ordinary two dimensional images from the rear of the cow, to obtain a silhouette image. Their study shows that it is possible to evaluate the body score automatically with an accuracy of the result at the same order of magnitude as the error of human evaluation.
Some extensive work on automated body condition scoring for dairy cattle was conducted by Coffey et al. at the Scottish Agricultural College. Light lines were created on the back of the cow by using a red laser light shone through a prism. The camera was positioned at a 45° angle to the horizontal plane of the cows back and the laser lines were used in manual extractions of curvatures over the cow's tailhead and buttocks. The curvature of these shapes was then modelled. The study found a large correlation, with a correlation coefficient of 0.55, between the tailhead curvature and observed BCS, whereas the correlation coefficient of the curvature of the right buttock as measured across the pin bone was 0.52.
An extensive study was produced by J. M. Bewley, A. M. Peacock, O. Lewis, R. E. Boyce, D. J. Roberts, M. P. Coffey, S. J. Kenyon, and M. M. Schutz “Potential for Estimation of Body Condition Scores in Dairy Cattle from Digital Images” Journal of Dairy Science, 91:3439-3453, 2008. Using digital images taken from above, the angles produced by the hook bones were extracted from a contour image. 99.89% of the automatically extracted body condition scores were within 0.5 points of actual score, and 89.95% were within 0.25 points.
In the study of the body condition score of Mediterranean buffaloes using ordinary two dimensional image analysis, P. Negretti, G. Bianconi, S. Bartocci, S. Terramoccia, and M. Verna in “Determination of live weight and body condition score in lactating Mediterranean buffalo by Visual Image Analysis” Livestock Science 113:1-7, 2008 confirmed that computerized image analysis is an effective measuring system. The Italian group also reached important conclusions showing that the automatic measurements of the angle between the back and the hook bones, and automatic measurements of the surface area behind the hook bones, where significantly correlated to the body condition score.
EP 1537531 discloses an imaging method and system for use in automatic monitoring the body condition of an animal. A predetermined region of interest on the animal body is imaged, and data indicative of the acquired one or more images is processed to obtain a three-dimensional representation of the region of interest. The three-dimensional representation is analyzed to determine a predetermined measurable parameter indicative of a surface relief of the region of interest which is indicative of the body condition of the imaged animal. The technique of the present invention is useful for determining the energy balance condition of the animal (e.g., dairy cow) or the tendency in the energy balance change, to thereby enable appropriately adjusting nutrition of the specific animal; as well as for determining the existence of in coordination and/or locomotion in the animal's natural marching.